1. Field of the Invention
The invention relates to a voxel-based transformation method, and more particularly to a voxel-based transformation method for a magnetic resonance imaging dataset.
2. Description of the Related Art
Diffusion MRI is a non-invasive imaging method suitable for evaluating fiber orientation of a specific region and revealing the underlying white matter structure of the human brain. By using the diffusion tensor model, diffusion MRI can be used to reconstruct diffusion tensor imaging (DTI), which has been used to study the fiber orientations and the quantitative measurement of the diffusion characteristics. The axonal connections in the human brain can also be assessed by applying streamline fiber tracking on DTI data.
However, DTI is based on an assumption that each voxel has only one nerve fiber, and therefore has the following limitations: difficulty in resolving crossing fibers and the partial volume effect, which leads to inaccurate estimation of anisotropy index at fiber crossing regions.
The crossing fiber limitation could be solved by using an orientation distribution function (ODF) to characterize the diffusion distribution. The diffusion images can be acquired by using high angular resolution diffusion image (HARDI) acquisition, or by using diffusion spectrum imaging (DSI) acquisition. Reconstruction methods include q-ball imaging (QBI) and DSI, which model diffusion distribution by a probability based approach and calculate diffusion ODFs, so as to obtain the fiber structure.
Although fiber crossing can be resolved using HARDI acquisition, one recent study showed that the generalized fractional anisotropy (GFA) offered by QBI is also vulnerable to the partial volume effect of crossing fibers, indicating that studies using ODF to characterize diffusion distribution may also suffer from the partial volume effect. This result can be explained by the fact that the ODF of the diffusion distribution (e.g., diffusion ODF) or fiber volume fraction (e.g., fiber orientation distribution, FOD) are fractional values, not the actual amount of the diffusion spins. The partial occupation of the crossing fibers or background diffusion will inevitably change the fractional values, leading to a consequence known as the partial volume effect.
Although the aforesaid methods for reconstructing the fiber orientation have been developed to a certain extent, they are still not good enough to reconstruct the fiber structure of an individual. Study and analysis of brain often need to transform data of the subjects to a standard space (e.g., template space) using a co-registration template to perform a linear or a non-linear diffeomorphic co-registration, so as to compare difference therebetween. Another method is to transform two data groups to the template space according to the same co-registration template to perform statistics analysis. In addition to comparing differences, a generated template related to multiple subjects can be constructed by averaging data of the subjects in the template space. The generated template is a new template integrating the aforesaid transformed MRI data of multiple subjects and including data of fiber orientation. This method may provide overall information of a human brain, and may play an important role in study of brain connectome.
To provide reliable overall information of the subjects is related to correct analysis of the fiber orientations from the generated template of the subjects, and to provide compatible quantitative analysis result.
Conventional developed methods of constructing a generated template related to multiple subjects are based on DTI. For further employing a method based on ODF in spatial transformation technique, it has been proposed to use HARDI to obtain transformed FOD. However, this method is limited by linear transformation, and the transformed FOD cannot provide an anisotropy index for quantitative analysis.
This problem is even more challenging when nonlinear transformation is applied to the ODF. The transformation may contain scaling and shearing that alter the fractional measurement of the diffusion spins and cause difficulties in transforming an ODF to the template space.